The present invention relates generally to the field of deep machine learning, and more particularly to deep machine learning applied to social networking function including the capturing, uploading, and captioning of images.
Deep learning is a branch of machine learning based on a set of algorithms that are designed to model high level abstractions in data by using a deep graph with multiple processing layers, composed of multiple linear and non-linear transformations. Deep learning is part of a broader family of machine learning methods based on learning representations of data. An observation, such as an image, can be represented in many ways, such as a vector of intensity values per pixel, or in a more abstract way such as a set of edges, and regions of particular shape. Some representations are better than others at simplifying the learning task, such as face recognition or facial expression recognition. One of the uses of deep learning is replacing handcrafted features with efficient algorithms for unsupervised or semi-supervised feature learning and hierarchical feature extraction. Research in this area attempts to make better representations and create models to learn these representations from large-scale unlabeled data. Various deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks.